Mining multi-dimensional constrained gradients in data cubes

Guozhu Dong, Jiawei Han, Joyce Lam, Jian Pei, Ke Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Constrained gradient analysis (similar to the "cubegrade" problem posed by Imielinski, et al. [9]) is to extract pairs of similar cell characteristics associated with big changes in measure in a data cube. Cells are considered similar if they are related by roll-up, drill-down, or 1-dimensional mutation operation. Constrained gradient queries are expressive, capable of capturing trends in data and answering "what-if" questions. To facilitate our discussion, we call one cell in a gradient pair probe cell and the other gradient cell. An efficient algorithm is developed, which pushes constraints deep into the computation process, finding all gradient-probe cell pairs in one pass. It explores bi-directional pruning between probe cells and gradient cells, utilizing transformed measures and dimensions. Moreover, it adopts a hyper-tree structure and an H-cubing method to compress data and maximize sharing of computation. Our performance study shows that this algorithm is efficient and scalable.

Original languageEnglish (US)
Title of host publicationVLDB 2001 - Proceedings of 27th International Conference on Very Large Data Bases
EditorsPeter M. G. Apers, Paolo Atzeni, Richard T. Snodgrass, Stefano Ceri, Kotagiri Ramamohanarao, Stefano Paraboschi
PublisherMorgan Kaufmann
Pages321-330
Number of pages10
ISBN (Electronic)1558608044, 9781558608047
StatePublished - 2001
Externally publishedYes
Event27th International Conference on Very Large Data Bases, VLDB 2001 - Roma, Italy
Duration: Sep 11 2001Sep 14 2001

Publication series

NameVLDB 2001 - Proceedings of 27th International Conference on Very Large Data Bases

Other

Other27th International Conference on Very Large Data Bases, VLDB 2001
Country/TerritoryItaly
CityRoma
Period9/11/019/14/01

ASJC Scopus subject areas

  • Information Systems and Management
  • Computer Science Applications
  • Hardware and Architecture
  • Software
  • Computer Networks and Communications
  • Information Systems

Fingerprint

Dive into the research topics of 'Mining multi-dimensional constrained gradients in data cubes'. Together they form a unique fingerprint.

Cite this